OXH AI – Open-Source AI Crypto Signal Platform with Real-Time Analysis

Hacker News

Hi HN! I built OXH AI - an AI-powered cryptocurrency signal platform that generates real-time trading signals using technical analysis and machine learning. What it does: - Generates AI trading signals for 100+ crypto pairs (Bitcoin, Ethereum, etc.) - Real-time technical indicator analysis (RSI, MACD, Bollinger Bands, EMA) - Risk scoring and position management - Auto-backtesting with historical data - Live chart integration with TradingView-style interface Why I built this: Most crypto signal platforms are either: 1. Black boxes with no transparency 2. Manual signals from "gurus" (often wrong) 3. Expensive ($100-500/month) I wanted something transparent, AI-driven, and affordable. Tech Stack: - Frontend: React + TypeScript + Vite - Backend: Node.js + Express + TypeScript - Database: Supabase (PostgreSQL) - AI: OpenAI GPT-4 for market analysis - Real-time: WebSocket for live updates - APIs: Binance, Bybit, OKX for price data Interesting Technical Challenges: 1. Race Condition Prevention: Implemented optimistic locking for Telegram auto-posting to prevent duplicate messages 2. Schema.org Optimization: Added LocalBusiness + Organization markup for better Google indexing 3. Rate Limiting: Built custom rate limiter that handles 50K+ API calls/day 4. Real-time Updates: WebSocket connections for live price & signal updates Features: - Free tier: 5 signals/day (no credit card) - Paid tier: Unlimited signals + advanced analytics - Referral system with leaderboard - Blog with auto-generated crypto content (2x daily) - Crypto news aggregation (updates every 2 hours) Privacy & Security: - No trading API keys stored (non-custodial) - Read-only market data - 2FA/MFA support - GDPR compliant What's Next: - Mobile app (React Native) - More exchanges (Kraken, Coinbase) - Advanced AI models (custom-trained on crypto data) - Social trading features Try it free: https://www.oxher.com Open to feedback and questions! What features would you find useful?

Visit product View on Hacker NewsOct 29, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRLess likely to generate early MRR · Strong signals: month, google, trading · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, model, google · Missing: agents, macos, agent

42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface, calls · Missing: plus, intuitive, reviews

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, cryptocurrency, paid · Missing: web3, chat, make money

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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